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Qualitative Comparison of Community Detection Algorithms [chapter]

Günce Keziban Orman, Vincent Labatut, Hocine Cherifi
2011 Communications in Computer and Information Science  
We then apply five community detection algorithms on these networks and find out the performance assessed quantitatively does not necessarily agree with a qualitative analysis of the identified communities  ...  It therefore seems both approaches should be applied to perform a relevant comparison of the algorithms.  ...  But more importantly, it is now possible to perform a qualitative comparison of the communities identified by different algorithms, instead of relying only on a single performance measure.  ... 
doi:10.1007/978-3-642-22027-2_23 fatcat:oznqoolndnbsbdb6ixq2y3sofi

A Distributed Bagging Ensemble Methodology for Community Prediction in Social Networks

Christos Makris, Georgios Pispirigos, Ioannis Orestis Rizos
2020 Information  
community detection algorithms has never been more essential.  ...  The proposed approach has been thoroughly tested, meticulously compared against different classic community detection algorithms, and practically proven exceptionally scalable, eminently efficient, and  ...  the comparison of the proposed methodology with the classic community detection algorithms of Louvain [10, 22] and Clauset-Newman-Moore [3, 25] .  ... 
doi:10.3390/info11040199 fatcat:rfp7eiqb4rfupnxac4si7r7jg4

Engineering Parallel Algorithms for Community Detection in Massive Networks

Christian L. Staudt, Henning Meyerhenke
2016 IEEE Transactions on Parallel and Distributed Systems  
To transform such data into useful information, fast analytics algorithms and software tools are necessary. One common graph analytics kernel is disjoint community detection (or graph clustering).  ...  Within this framework we design and implement efficient parallel community detection heuristics: A parallel label propagation scheme; the first large-scale parallelization of the well-known Louvain method  ...  Comparison with State-of-the-Art Competitors In this section we present results for an experimental comparison with several relevant competing community detection codes.  ... 
doi:10.1109/tpds.2015.2390633 fatcat:b24piu4j2fc7bk4hknq4wo4lny

Networked Grounded Theory

Alexios Brailas
2014 The Qualitative Report  
This method was developed during my PhD research on the utilization of a virtual community (case study in Wikipedia) in formal Education institutions (tertiary or secondary education).  ...  Networked Grounded Theory constitutes a remodeling of Grounded Theory and the rationale for the inclusion of Network Analysis techniques into the process of theory generation is explained.  ...  I would like to express my deep gratitude to Professor Konstantinos Koskinas, my PhD supervisor, for his enthusiastic encouragement and useful critiques of this research work.  ... 
doi:10.46743/2160-3715/2014.1270 fatcat:yioyy2mj2befjkhl6fh4b2uaue

An Empirical Comparison of the Summarization Power of Graph Clustering Methods [article]

Yike Liu, Neil Shah, Danai Koutra
2015 arXiv   pre-print
Graph clustering or community detection algorithms can summarize a graph in terms of coherent and tightly connected clusters.  ...  technique, in the heart of which lies the k-core algorithm (iii) Evaluation: We compare the summarization power of five clustering techniques on large real graphs, and analyze their compression performance  ...  Table 2 : 2 Qualitative comparison of the clustering techniques.  ... 
arXiv:1511.06820v1 fatcat:ogyj4eus6rh5zec77argqp45ry

Detection of Camouflaged People

Bento NA, Silva JS
2016 International Journal of Sensor Networks and Data Communications  
The use of thermal imaging is a benefit for the military people. Due to their advantages, it has a large number of applications, including the detection of camouflaged people.  ...  The values obtained support the conclusions extracted from the qualitative analysis.  ...  Zheng [5] makes a comparison of multi-scale pixel level fusion algorithms, such as: Different Pyramids, Discrete Wavelet Transform (DWT) and Iterative DWT.  ... 
doi:10.4172/2090-4886.1000143 fatcat:pbqzjqdmyrci3nensya7mgvyt4

A general framework for complex network-based image segmentation

Youssef Mourchid, Mohammed El Hassouni, Hocine Cherifi
2019 Multimedia tools and applications  
Experiments are conducted on Berkeley Segmentation Dataset and four of the most influential community detection algorithms are tested.  ...  If we consider regions as communities, using community detection algorithms directly can lead to an over-segmented image.  ...  Comparison between the proposed community detection algorithms In this section, we compare the proposed community detection algorithms, to choose the best of them for the next comparison with the state  ... 
doi:10.1007/s11042-019-7304-2 fatcat:iw46gldhprgxjot2lcvgzzdvi4

Detecting moving shadows: algorithms and evaluation

A. Prati, I. Mikic, M.M. Trivedi, R. Cucchiara
2003 IEEE Transactions on Pattern Analysis and Machine Intelligence  
classes of algorithms on a benchmark suite of indoor and outdoor video sequences.  ...  These video sequences and associated "ground-truth" data are made available at to allow for others in the community to experiment with new algorithms and metrics.  ...  Ivana Mikic was with the Computer Vision and Robotics Department of Electrical and Computer Engineering, University of California, San Diego.  ... 
doi:10.1109/tpami.2003.1206520 fatcat:uevg2q6fevaqbi55gg4gl4r7xy

Modularity-Based Image Segmentation

Shijie Li, Dapeng Oliver Wu
2015 IEEE transactions on circuits and systems for video technology (Print)  
When the modularity of the segmented image is maximized, the algorithm stops merging and produces the final segmented image.  ...  To address the problem of segmenting an image into sizeable homogeneous regions, this paper proposes an efficient agglomerative algorithm based on modularity optimization.  ...  Fig. 8 . 8 Qualitative comparison of segmentation results by some popular methods.  ... 
doi:10.1109/tcsvt.2014.2360028 fatcat:o3ojl3btabd4bhqb6qd2t4bgwq

Automated landmarking of bends in vascular structures: a comparative study with application to the internal carotid artery

Henrik A Kjeldsberg, Aslak W Bergersen, Kristian Valen-Sendstad
2021 BioMedical Engineering OnLine  
Applying the algorithms to the same cohort revealed a variability that makes comparison of results between previous studies questionable.  ...  The two existing algorithms rely on numerical approximations of curvature and torsion of the centerline.  ...  Marina Piccinelli for providing insight into the landmarking algorithm, and suggested values for input parameters.  ... 
doi:10.1186/s12938-021-00957-6 pmid:34838018 pmcid:PMC8626959 fatcat:tsyqy5nwxrguvpwosw7u2z7gxu

An Extended Occlusion Detection Approach for Video Processing

Synh Viet-Uyen Ha, Tuan-Anh Vu, Ha Manh Tran
2018 REV Journal on Electronics and Communications  
This paper presents the work in process approach that can detect occlusion regions by using pixel-wise coherence, segment-wise confidence and interpolation technique.  ...  The accuracy at the boundaries of the moving objects is one of the challenging areas that required further exploration and research.  ...  Qualitative and quantitative evaluations of the proposed algorithm have been carried out.  ... 
doi:10.21553/rev-jec.198 fatcat:ipocxfmbqncmlgy3osjfoy43ge

Parallel heuristics for scalable community detection

Hao Lu, Mahantesh Halappanavar, Ananth Kalyanaraman
2015 Parallel Computing  
Community detection has become a fundamental operation in numerous graph-theoretic applications.  ...  In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template.  ...  A preliminary version of this paper appeared in [11] .  ... 
doi:10.1016/j.parco.2015.03.003 fatcat:2lgpvrqcivht3ggmwaplh2ib4q

Compared Insights on Machine-Learning Anomaly Detection for Process Control Feature

Ming Wan, Quanliang Li, Jiangyuan Yao, Yan Song, Yang Liu, Yuxin Wan
2022 Computers Materials & Continua  
In the verified experiments, two attack models and four different attack intensities are defined to facilitate all quantitative comparisons, and the impacts of detection accuracy caused by the feature  ...  algorithm.  ...  Differences of Qualitative Properties Under different circumstances, various machine-learning algorithms present differential detection performances, that is, each machine-learning algorithm can develop  ... 
doi:10.32604/cmc.2022.030895 fatcat:52catibmrna7ldxldhltdc7z2u

Empirical Comparison of Algorithms for Network Community Detection [article]

Jure Leskovec, Kevin J. Lang, Michael W. Mahoney
2010 arXiv   pre-print
Considering community quality as a function of its size provides a much finer lens with which to examine community detection algorithms, since objective functions and approximation algorithms often have  ...  Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest.  ...  Notice the qualitative shape of the NCP plots remains practically unchanged regardless of what particular community detection algorithm we use.  ... 
arXiv:1004.3539v1 fatcat:7mqfcpefcnhf5htvdfrgzbleom

Empirical comparison of algorithms for network community detection

Jure Leskovec, Kevin J. Lang, Michael Mahoney
2010 Proceedings of the 19th international conference on World wide web - WWW '10  
Considering community quality as a function of its size provides a much finer lens with which to examine community detection algorithms, since objective functions and approximation algorithms often have  ...  Detecting clusters or communities in large real-world graphs such as large social or information networks is a problem of considerable interest.  ...  Notice the qualitative shape of the NCP plots remains practically unchanged regardless of what particular community detection algorithm we use.  ... 
doi:10.1145/1772690.1772755 dblp:conf/www/LeskovecLM10 fatcat:w4ery4mwpvacbhjscv73w727ry
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